Identification of collaborative driver pathways in breast cancer.
Identification of collaborative driver pathways in breast cancer.
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DOI：
10.1186/1471-2164-15-605
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发表时间：
2014-07-17
期刊：
影响因子：
4.4
通讯作者：
Hu Z
中科院分区：
文献类型：
--
作者：
Liu Y;Hu Z
癌症生物学的一个重要挑战是通过计算筛选癌细胞中的突变，将那些可能导致癌症发生和发展的突变与大量的旁观者分开。由于突变的数量大，类型多样，因此一组样本中任何特定突变模式的频率都很低。这使得不同人群之间的统计差异和重复性难以建立。在本文中，我们开发了一种新的方法，有望部分改善这些问题。其基本思想是，虽然突变是高度异质性的，并且从一个样本到另一个样本都有所不同，但当细胞发生转化时被破坏的过程在特定癌症或癌症亚型的人群中往往是不变的。具体来说，我们专注于寻找突变的通路组，这些通路组在乳腺癌亚型的样本中是不变的。信息通路组的识别包括两个步骤。第一个是识别显著富集含有非同义突变的基因的途径;第二个使用如此识别的途径来找到在最大数量的样品中功能相关的组。一个应用程序，以4亚型的乳腺癌确定的路径组，可以高度解释一个特定的亚型和丰富的过程与转化。与以前的方法相比，在没有任何进一步验证的情况下，在一组样本中识别通路，我们表明，突变的通路组可以在每个乳腺癌亚型中找到，并且这些组在大多数样本中是不变的。该算法可在http://www.visantnet.org/misi/MUDPAC.zip上获得。本文的在线版本（doi：10.1186/1471-2164-15-605）包含补充材料，可供授权用户使用。
An important challenge in cancer biology is to computationally screen mutations in cancer cells, separating those that might drive cancer initiation and progression, from the much larger number of bystanders. Since mutations are large in number and diverse in type, the frequency of any particular mutation pattern across a set of samples is low. This makes statistical distinctions and reproducibility across different populations difficult to establish. In this paper we develop a novel method that promises to partially ameliorate these problems. The basic idea is although mutations are highly heterogeneous and vary from one sample to another, the processes that are disrupted when cells undergo transformation tend to be invariant across a population for a particular cancer or cancer subtype. Specifically, we focus on finding mutated pathway-groups that are invariant across samples of breast cancer subtypes. The identification of informative pathway-groups consists of two steps. The first is identification of pathways significantly enriched in genes containing non-synonymous mutations; the second uses pathways so identified to find groups that are functionally related in the largest number of samples. An application to 4 subtypes of breast cancer identified pathway-groups that can highly explicate a particular subtype and rich in processes associated with transformation. In contrast to previous methods that identify pathways across a set of samples without any further validation, we show that mutated pathway-groups can be found in each breast cancer subtype and that such groups are invariant across the majority of samples. The algorithm is available at http://www.visantnet.org/misi/MUDPAC.zip. The online version of this article (doi:10.1186/1471-2164-15-605) contains supplementary material, which is available to authorized users.
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影响因子：
14.9
作者：
Gonzalez-Perez A;Lopez-Bigas N
通讯作者：
Lopez-Bigas N
影响因子：
50.3
作者：
De Carvalho DD;Sharma S;You JS;Su SF;Taberlay PC;Kelly TK;Yang X;Liang G;Jones PA
通讯作者：
Jones PA
影响因子：
3.7
作者：
Cerami E;Demir E;Schultz N;Taylor BS;Sander C
通讯作者：
Sander C
DOI：
10.1158/1078-0432.ccr-08-3293
发表时间：
2009-06-01
期刊：
Clinical cancer research : an official journal of the American Association for Cancer Research
影响因子：
--
作者：
Agarwal R;Gonzalez-Angulo AM;Myhre S;Carey M;Lee JS;Overgaard J;Alsner J;Stemke-Hale K;Lluch A;Neve RM;Kuo WL;Sorlie T;Sahin A;Valero V;Keyomarsi K;Gray JW;Borresen-Dale AL;Mills GB;Hennessy BT
通讯作者：
Hennessy BT
影响因子：
12.3
作者：
Bashashati A;Haffari G;Ding J;Ha G;Lui K;Rosner J;Huntsman DG;Caldas C;Aparicio SA;Shah SP
通讯作者：
Shah SP